| Action2Activity: recognizing complex activities from sensor data Y Liu, L Nie, L Han, L Zhang, DS Rosenblum arXiv preprint arXiv:1611.01872, 2016 | 391 | 2016 |
| Gated fully fusion for semantic segmentation X Li, H Zhao, L Han, Y Tong, S Tan, K Yang Proceedings of the AAAI conference on artificial intelligence 34 (07), 11418 …, 2020 | 227 | 2020 |
| Parametrized deep q-networks learning: Reinforcement learning with discrete-continuous hybrid action space J Xiong, Q Wang, Z Yang, P Sun, L Han, Y Zheng, H Fu, T Zhang, J Liu, ... arXiv preprint arXiv:1810.06394, 2018 | 218 | 2018 |
| Liir: Learning individual intrinsic reward in multi-agent reinforcement learning Y Du, L Han, M Fang, J Liu, T Dai, D Tao Advances in Neural Information Processing Systems 32, 2019 | 191 | 2019 |
| Curriculum-guided hindsight experience replay M Fang, T Zhou, Y Du, L Han, Z Zhang Advances in neural information processing systems 32, 2019 | 171 | 2019 |
| Exponentially Weighted Imitation Learning for Batched Historical Data Q Wang, J Xiong, L Han, P Sun, H Liu, T Zhang The Thirty-second Annual Conference on Neural Information Processing Systems …, 2018 | 119 | 2018 |
| Tstarbots: Defeating the cheating level builtin ai in starcraft ii in the full game P Sun, X Sun, L Han, J Xiong, Q Wang, B Li, Y Zheng, J Liu, Y Liu, H Liu, ... arXiv preprint arXiv:1809.07193, 2018 | 80 | 2018 |
| Learning multi-level task groups in multi-task learning L Han, Y Zhang Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 70 | 2015 |
| Rethinking goal-conditioned supervised learning and its connection to offline rl R Yang, Y Lu, W Li, H Sun, M Fang, Y Du, X Li, L Han, C Zhang arXiv preprint arXiv:2202.04478, 2022 | 65 | 2022 |
| Rorl: Robust offline reinforcement learning via conservative smoothing R Yang, C Bai, X Ma, Z Wang, C Zhang, L Han Advances in neural information processing systems 35, 23851-23866, 2022 | 63 | 2022 |
| Grid-wise control for multi-agent reinforcement learning in video game ai L Han, P Sun, Y Du, J Xiong, Q Wang, X Sun, H Liu, T Zhang International Conference on Machine Learning, 2576-2585, 2019 | 63 | 2019 |
| Learning tree structure in multi-task learning L Han, Y Zhang Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015 | 51 | 2015 |
| Multi-Stage Multi-Task Learning with Reduced Rank L Han, Y Zhang Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 48 | 2016 |
| Principled exploration via optimistic bootstrapping and backward induction C Bai, L Wang, L Han, J Hao, A Garg, P Liu, Z Wang International Conference on Machine Learning, 577-587, 2021 | 43 | 2021 |
| Local uncertainty sampling for large-scale multiclass logistic regression L Han, KM Tan, T Yang, T Zhang | 38 | 2020 |
| Tstarbot-x: An open-sourced and comprehensive study for efficient league training in starcraft ii full game L Han, J Xiong, P Sun, X Sun, M Fang, Q Guo, Q Chen, T Shi, H Yu, X Wu, ... arXiv preprint arXiv:2011.13729, 2020 | 32 | 2020 |
| Encoding tree sparsity in multi-task learning: A probabilistic framework L Han, Y Zhang, G Song, K Xie Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014 | 32 | 2014 |
| Exploit reward shifting in value-based deep-rl: Optimistic curiosity-based exploration and conservative exploitation via linear reward shaping H Sun, L Han, R Yang, X Ma, J Guo, B Zhou Advances in neural information processing systems 35, 37719-37734, 2022 | 27 | 2022 |
| Dynamic bottleneck for robust self-supervised exploration C Bai, L Wang, L Han, A Garg, J Hao, P Liu, Z Wang Advances in Neural Information Processing Systems 34, 17007-17020, 2021 | 24 | 2021 |
| MHER: Model-based hindsight experience replay R Yang, M Fang, L Han, Y Du, F Luo, X Li arXiv preprint arXiv:2107.00306, 2021 | 23 | 2021 |
Tong ZhangUIUCVerified email at tongzhang-ml.org
